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CASE STUDY / 06

Untangling a critical prompt-composition path.

Principal investigation and implementation of prompt-rendering and chat-load improvements, separating reusable agent behavior from organization-specific instructions.

Production delivery

Rails / Liquid / RubyLLM · anonymized learning platform

Outcome Released functionality; production performance impact was not quantified.

The problem

Prompt composition mixed rendering, context loading, and snippet resolution. Chat loading could rebuild prompts and repeat database lookups; shared agent prompts embedded organization-specific instructions.

My contribution

Shipped native Liquid partial rendering, avoided unnecessary rebuilding during chat loading, reduced repeated lookups, and composed organization context around reusable agent behavior.

The boundary

Further decomposition and cache-freshness work was staged or proposed. Separate local benchmarks do not establish shipped production latency or cost improvements.

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